Sandra Eickmeier

Dynamic factor models

SummaryFactor models can cope with many variables without running into scarce degrees of freedom problems often faced in a regression-based analysis. In this article we review recent work on dynamic factor models that have become popular in macroeconomic policy analysis and forecasting. By means of an empirical application we demonstrate that these models turn out to be usefu in investigating macroeconomic problems.

How synchronized are new EU member states with the euro area? Evidence from a structural factor model

A high degree of cyclical synchronization between the new EU member states (NMS) from central and eastern Europe and the euro area is generally seen as a prerequisite for successful EMU enlargement. This paper investigates comovements between NMS and the euro area. We first establish stylized facts on economic linkages using dynamic correlation and cohesion measures. We then identify the main structural common euro-area shocks and investigate their transmission to the NMS in comparison to the current EMU members by means of a large-scale dynamic factor model. Overall, our results are mixed. Dynamic business cycle and inflation correlations between NMS and the euro area are, on average, lower than between individual EMU members and the euro area, but they are higher than for some small peripheral EMU countries. This is confirmed by our other measure, variance shares of output and inflation explained by common euro-area factors. The proliferation of euro-area shocks to the NMS does not differ significantly from the propagation to EMU countries in most cases. There seems to be considerable heterogeneity across NMS, implying that for some countries, accession to EMU would be more costly than for others. According to our analysis and based on our measures, Poland, Slovenia, Hungary and Estonia are more suitable EMU candidates than other countries.

Monetary Policy, Housing Booms and Financial (Im)Balances

This paper uses a factor-augmented vector autoregressive model (FAVAR) estimated on U.S. data in order to analyze monetary transmission via private sector balance sheets, credit risk spreads and asset markets in an integrated setup and to explore the role of monetary policy in the three imbalances that were observed prior to the global financial crisis: high house price inflation, strong private debt growth and low credit risk spreads. The results suggest that (i) monetary policy shocks have a highly significant and persistent effect on house prices, real estate wealth and private sector debt as well as a strong short-lived effect on risk spreads in the money and mortgage markets; (ii) monetary policy shocks have contributed discernibly, but at a late stage to the unsustainable developments in house and credit markets that were observable between 2001 and 2006; (iii) financial shocks have influenced the path of policy rates prior to the crisis, and the feedback effects of financial shocks via lower policy rates on property and credit markets are found to have probably been considerable.

The Global Dimension of Inflation: Evidence from Factor-Augmented Phillips Curves

We examine the global dimension of inflation in 24 OECD countries between 1980 and 2007 in a traditional Phillips curve framework. We decompose output gaps and changes in unit labor costs into common (or global) and idiosyncratic components using a factor analysis and introduce these components separately in the regression. Unlike previous studies, we allow global forces to affect inflation through (the common part of) domestic demand and supply conditions. Our most important result is that the common component of changes in unit labor costs notably affects inflation. We also find evidence that movements in import price inflation have small effects on CPI inflation while the impact of movements in the common component of the output gap is unclear. A counterfactual experiment illustrates that the common component of unit labor cost changes and non-commodity import price inflation have held down overall inflation in many countries in recent years. Our results imply that monetary policy makers need to carefully monitor global forces when assessing and predicting inflation. In analogy to the Phillips curves, we estimate monetary policy rules with common and idiosyncratic components of inflation and the output gap included separately. Central banks have indeed reacted to the global components.

Common stationary and non-stationary factors in the euro area analyzed in a large-scale factor model

In this paper we rely on techniques recently developed by Bai and Ng (2004a) to estimate common euro-area stationary and non-stationary factors using a large-scale dynamic factor model. We find that euro-area economies share four non-stationary factors or trends and one stationary factor. By means of rotation techniques, we estimate a euro-area business cycle which is a fairly good match to EuroCOIN, the euro-area coincident business cycle indicator published by the CEPR. Fluctuations of common euro-area factors mainly reflect variations of German and French real economic activity as well as of producer prices and financial prices (long-term interest rates and/or real effective exchange rates) in various countries. As concerns the transmission channels, macroeconomic shocks seem to proliferate in the euro area more strongly through trade, exchange rates and long-term interest rates than through stock prices. Among the external driving forces, shocks to US economic activity seem to be more strongly linked to shocks to the euro-area factors than oil price shocks. We finally find evidence of mild overall convergence; results for individual countries are mixed.

Analyzing Business and Financial Cycles Using Multi-Level Factor Models

This paper compares alternative estimation procedures for multi-level factor models which imply blocks of zero restrictions on the associated matrix of factor loadings. We suggest a sequential least squares algorithm for minimizing the total sum of squared residuals and a two-step approach based on canonical correlations that are much simpler and faster than Bayesian approaches previously employed in the literature. Monte Carlo simulations suggest that the estimators perform well in typical sample sizes encountered in the factor analysis of macroeconomic data sets. We apply the methodologies to study international comovements of business and financial cycles as well as asymmetries over the business cycle in the US.

Time-varying Volatility, Financial Intermediation and Monetary Policy

We document that expansionary monetary policy shocks are less effective at stimulating output and investment in periods of high volatility compared to periods of low volatility, using a regime-switching vector autoregression. Exogenous policy changes are identified by adapting an external instruments approach to the non-linear model. The lower effectiveness of monetary policy can be linked to weaker responses of credit costs, suggesting a financial accelerator mechanism that is weaker in high volatility periods. To rationalize our robust empirical results, we use a macroeconomic model in which financial intermediaries endogenously choose their capital structure. In the model, the leverage choice of banks depends on the volatility of aggregate shocks. In low volatility periods, financial intermediaries lever up, which makes their balance sheets more sensitive to aggregate shocks and the financial accelerator more effective. On the contrary, in high volatility periods banks decrease leverage, which renders the financial accelerator less effective; this in turn decreases the ability of monetary policy to improve funding conditions and credit supply, and thereby to stimulate the economy. Hence, we provide a novel explanation for the non-linear effects of monetary stimuli observed in the data, linking the effectiveness of monetary policy to the procyclicality of leverage.

Monetary policy and the oil futures market

We assess the transmission of monetary policy shocks on oil prices using a VAR model. We identify monetary policy and financial activity shocks disentangled from demand and oil supply shocks using sign restrictions. We obtain the following main findings. (i) Monetary policy and financial activity shocks both have a significant effect on the oil price. (ii) Monetary policy has made large positive contributions to oil price growth in 2008. (iii) Monetary policy affects the oil price primarily through fundamental (supply and demand) channels rather than through financial activity.